Joint Vehicular Localization and Reflective Mapping Based on Team Channel-SLAM
Xinghe Chu, Zhaoming Lu, David Gesbert, Luhan Wang, Xiangming Wen,, Muqing Wu, Meiling Li

TL;DR
This paper introduces TCSE, a novel method that jointly localizes vehicles and maps reflecting surfaces using Team Channel-SLAM, significantly improving high-resolution vehicle positioning by exploiting shared radio propagation paths.
Contribution
The paper presents the first integration of joint localization and reflective surface mapping within a mobile networking framework using radio data, enhancing vehicle tracking accuracy.
Findings
TCSE achieves high-resolution vehicle localization.
Joint mapping of reflecting surfaces improves accuracy.
Provides a complete picture of radio path trajectories.
Abstract
This paper addresses high-resolution vehicle positioning and tracking. In recent work, it was shown that a fleet of independent but neighboring vehicles can cooperate for the task of localization by capitalizing on the existence of common surrounding reflectors, using the concept of Team Channel-SLAM. This approach exploits an initial (e.g. GPS-based) vehicle position information and allows subsequent tracking of vehicles by exploiting the shared nature of virtual transmitters associated to the reflecting surfaces. In this paper, we show that the localization can be greatly enhanced by joint sensing and mapping of reflecting surfaces. To this end, we propose a combined approach coined Team Channel-SLAM Evolution (TCSE) which exploits the intertwined relation between (i) the position of virtual transmitters, (ii) the shape of reflecting surfaces, and (iii) the paths described by the…
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Taxonomy
TopicsUAV Applications and Optimization · Indoor and Outdoor Localization Technologies · Vehicular Ad Hoc Networks (VANETs)
